BOL: Related items

The Mills lab

Wed, 24 Feb 2016 16:18:38 -0600

The laboratory is focused on the discovery and analysis of structural variation (SVs) from genomic sequence data. As part of the 1000 Genomes Project and other endeavors, we have helped produce initial fine-scale maps using a variety of SV discovery approaches including: (i) paired-end mapping (or read pair analysis) based on abnormally mapped pairs of clone ends; (ii) read-depth analysis, which detects deletions and duplications through analysis of the read depth-of-coverage; (iii) split read analysis, which detects SVs by evaluating gapped sequence alignments; and (iv) sequence assembly, which enables the discovery of novel (non-reference) sequence insertions.

http://millslab.org/research.html

PASA: Gene Structure Annotation and Analysis

biogeek — Tue, 26 Dec 2017 21:14:03 -0600

PASA, acronym for Program to Assemble Spliced Alignments, is a eukaryotic genome annotation tool that exploits spliced alignments of expressed transcript sequences to automatically model gene structures, and to maintain gene structure annotation consistent with the most recently available experimental sequence data. PASA also identifies and classifies all splicing variations supported by the transcript alignments.

Address of the bookmark: http://pasapipeline.github.io/

GenomeThreader: Gene Prediction Software

Neel — Wed, 03 Oct 2018 15:34:08 -0500

GenomeThreader is a software tool to compute gene structure predictions. The gene structure predictions are calculated using a similarity-based approach where additional cDNA/EST and/or protein sequences are used to predict gene structures via spliced alignments. GenomeThreader was motivated by disabling limitations in GeneSeqer, a popular gene prediction program which is widely used for plant genome annotation.

Address of the bookmark: http://genomethreader.org/

MimiLook: A Phylogenetic Workflow for Detection of Gene Acquisition in Major Orthologous Groups of Megavirales

Abhi — Mon, 10 Jan 2022 06:32:22 -0600

This tool detects statistically validated events of gene acquisitions with the help of the T-REX algorithm by comparing individual gene tree with NCBI species tree. In between the steps, the workflow decides about handling paralogs, filtering outputs, identifying Megavirale specific OGs, detection of HGTs, along with retrieval of information about those OGs that are monophyletic with organisms from cellular domains of life.

https://www.readcube.com/articles/10.3390%2Fv9040072

Address of the bookmark: https://pubmed.ncbi.nlm.nih.gov/28387730/

Tigers genome sequenced

Rahul Agarwal — Tue, 17 Sep 2013 16:48:24 -0500

Fifteen scientists led by Dr Jong Bhak of Genome Research Foundation, South Korea, decoded as many as 3 billion nucleotides (organic molecules that form the basic building blocks of nucleic acids, such as DNA). They identified 20,000 genes related to various functions of the tiger.

The biggest and perhaps most fearsome of the world's big cats, the tiger, shares 95.6 percent of its DNA with humans' cute and furry companions, domestic cats.

The new research showed that big cats have genetic mutations that enabled them to be carnivores. The team also identified mutations that allow snow leopards to thrive at high altitudes.

Reference:

http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690

http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms

Paper:

http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html

EGAD: Ultra-fast functional analysis of gene networks

Rahul Nayak — Fri, 14 Dec 2018 04:10:35 -0600

With the EGAD (Extending ‘Guilt-by-Association’ by Degree) package, we present a series of highly efficient tools to calculate functional properties in networks based on the guilt-by-association principle. These allow rapid controlled comparisons and analyses. Two of the core features are: a function prediction algorithm which is fully vectorized (neighbor_voting), allowing network characterization across even thousands of functional groups to be accomplished in minutes in cross-validation and an analytic determination of the optimal prior to guess candidates genes across multiple functional sets (calculate_multifunc, auc_multifunc).

Address of the bookmark: https://github.com/sarbal/EGAD

gggenes: a ggplot2 extension for drawing gene arrow maps.

BioStar — Tue, 02 Jun 2020 11:43:34 -0500

Install the stable version of gggenes from CRAN:

install.packages("gggenes")

If you want the development version, install it from GitHub:

devtools::install_github("wilkox/gggenes")

More at https://github.com/wilkox/gggenes

Address of the bookmark: http://wilkox.org/gggenes

MetaEuk - sensitive, high-throughput gene discovery and annotation for large-scale eukaryotic metagenomics

Jit — Wed, 13 Jan 2021 19:29:32 -0600

MetaEuk is a modular toolkit designed for large-scale gene discovery and annotation in eukaryotic metagenomic contigs. Metaeuk combines the fast and sensitive homology search capabilities of MMseqs2 with a dynamic programming procedure to recover optimal exons sets. It reduces redundancies in multiple discoveries of the same gene and resolves conflicting gene predictions on the same strand. MetaEuk is GPL-licensed open source software that is implemented in C++ and available for Linux and macOS. The software is designed to run on multiple cores.

Address of the bookmark: https://github.com/soedinglab/metaeuk

Translational Bioinformatics: Transforming 300 Billion Points of Data

Tue, 20 Aug 2013 19:03:47 -0500

Translational Bioinformatics: Transforming 300 Billion Points of Data into Diagnostics, Therapeutics, and New Insights into Disease Air date: Wednesday, June 20, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Description: There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations haven't been well described. The nascent field of translational bioinformatics may help. Dr. Butte's lab at Stanford University builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data (measured by researchers and clinicians over the past decade) into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his lab's work on using publicly available molecular measurements to find new uses for drugs, discovering new treatable mechanisms of disease in type 2 diabetes, and evaluating patients presenting with whole genomes sequenced. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Atul Butte, M.D., Ph.D., Stanford University Runtime: 01:07:42 Permanent link: http://videocast.nih.gov/launch.asp?17321

ANGES: reconstructing ANcestral GEnomeS maps

Abhimanyu Singh — Thu, 18 May 2017 05:27:08 -0500

This page contains the software ANGES 1.01, that aims at reconstucting ancestral genome maps from homologous markers in extant related genomes.

Download

Program, version 1.01 (July 10, 2012, documentation updated in August 2014)
Examples with results (featured ancestors: boreoeutherian, amniote, yeasts, Burkholderia, monocots); please refer to the documentation of the distribution above.

Address of the bookmark: http://paleogenomics.irmacs.sfu.ca/ANGES/